# deeplearning.ai

**Repository Path**: winter_master/deeplearning.ai

## Basic Information

- **Project Name**: deeplearning.ai
- **Description**: Some work of Andrew Ng's course on Coursera
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2020-02-07
- **Last Updated**: 2020-12-18

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# deepleraning.ai-course
This is some records of Andrews' `deeplearning.ai` course from `Coursera`. I have uploaded my programming implement to this warehouse. There might be something wrong with my work, be free to email `zpzhang1995@gmail.com`. And if you can push your right answer, that will be grateful.<br/>
And to be clear, Ng's course is my first access to AI. I would love to share more learning experience on DL/ML, so I will put some good repos/articles on this page. Please read this whole `REDEME`, hope there is some thing helps you. <br/>
Read AI article on my [blog](https://judasdie.github.io/)

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### Course Contents
**Neural Networks and Deep Learning**  
<font size=1>Week1　Introduction to deep learning</font>  
<font size=1>Week2　Neural Networks Basics</font>   
<font size=1>Week3　Shallow Neural networks</font>   
<font size=1>Week4　Deep Neural Networks</font>   

**Improving Deep Neural Networks**  
<font size=1>Week1　Practical aspects of Deep Learning(Initialization-Regularization-Gradient Checking)</font>  
<font size=1>Week2　Optimization algorithms</font>  
<font size=1>Week3　Hyperparameter tuning, Batch Normalization and Programming Frameworks</font>  

**Convolutional Neural Network**  
<font size=1>Week1　Foundations of Convolutional Neural Networks</font>  
<font size=1>Week2　Deep convolutional models: case studies</font>  
<font size=1>Week3　Object detection</font>  
<font size=1>Week4　Special applications: Face recognition & Neural style transfer</font>  
   
**Sequence Models**  
<font size=1>Week1　Recurrent Neural Networks</font>  
<font size=1>Week2　Natural Language Processing & Word Embeddings</font>  
<font size=1>Week3　Sequence models & Attention mechanism</font>  
   
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**Blog Articles**  
- [How to build Github Pages with jeklly](https://judasdie.github.io/2018/04/use-jeklly-build-githubpages/)
- [Three ways for face detection](https://judasdie.github.io/2018/04/three-ways-for-face-detection/)
- [Real Time Film-Lead Face Identify](https://judasdie.github.io/2018/04/real-time-film-lead-face-identify/)

------

### About install tensorflow-gpu on windows
- Cause I found many people get many issues while installing tensorflow-gpu on windows, and there are many talks before tensorflow-1.4.0 shows like this on [Stackoverflow](https://stackoverflow.com/questions/42011070/on-windows-running-import-tensorflow-generates-no-module-named-pywrap-tenso).   
- You will not face problem above again thanks to tensorflow-1.4.0!  
-  **python3.6.x + cudnn6.0 + CUDA8.0 + tensorflow-1.4.0** work perfect!
- Remember move files in cundnn to CUDA8.0 accordingly (you also do this in the past)!

-----
### Learn Tensorflow and Deep Neural Network
- I recommend you a video course for learning tensorflow from Google [here](http://pan.baidu.com/s/1ge2xPuF)
- A good introduction about Deep Neural Network, download [here](http://pan.baidu.com/s/1c1FviBA) <br/>
- Best results on standard dataset like MNIST, CIFAR-10/100, ILSVRC2012... [here](http://rodrigob.github.io/are_we_there_yet/build/)<br/>
- Keras Documentation Chinese Version [here](https://pan.baidu.com/s/1dGsZPRj)<br/>
- Deep Learning by Goodfellow [here](https://pan.baidu.com/s/1sm0dvBn)
### Some Good Machine Learning Tutorial
- Expectation Maximization(EM) course by Xu Yida on [Youtube](https://www.youtube.com/watch?v=Bq5s80ZCmC0&list=PLyAft-JyjIYpno8IfZZS0mnxD5TYZ6BIc)<br/>
- Understanding Variational Autoencoders ([VAEs](https://jaan.io/what-is-variational-autoencoder-vae-tutorial/)) from two perspectives: deep learning and graphical models

### Some good repo
- GANs with keras [here](https://github.com/eriklindernoren/Keras-GAN)<br/>
- GANs with pytorch [here](https://github.com/eriklindernoren/PyTorch-GAN)

-----
### Update Records
- Specialization 4 Done!　2017/11/13
- Move Course Records to Records.md　2017/11/14
- Add Expectation Maximization(EM) course links　2017/12/13
- Add a Chinese Version keras tutorial　2018/2/23
- Specialization 5 Done!　2018/3/8
- Add GANs repo  2018/5/13


### Thanks for Andrew Ng!